The Role of Data Mining Every Business Person Must Know

With the scope of data that companies have to handle every day, it was only logical to see data management practices growing more complicated year after year. Meanwhile, the importance of data mining in business has also increased.

Data management encompasses various practices, including acquiring, validating, and storing data. All this is done so that businesses can have access to reliable data and be able to make informed business decisions. The recent statistics back this up. For instance, 95% of C-level executives see data as a critical asset when making a business strategy. On top of that, 50% of companies have data integration projects planned in the next year.

Data mining is one of the most critical processes of data management, and to bring this concept closer to you, we have laid out the role of data mining.
The Role of Data Mining in Business

As the business environment becomes more competitive each day, so does the importance of data mining in business. Why? Because data mining plays a vital role in the success of Business Intelligence strategies, its primary purpose is to help businesses examine big chunks of data, and get their hands on useful and actionable information.

Data mining if implemented correctly can help businesses get a competitive advantage, penetrate new markets, grow, increase sales, and improve customer relationships. This is achieved via the discovery of essential rules and patterns hidden in data. These patterns and practices help business predict future outcomes and plan accordingly.

So far, we have seen data mining help companies achieve their goals in all verticals. Data mining has been of use in direct marketing, customer relationship management (CRM), e-commerce, the health industry, FMCG industry, financial sector, and the telecommunication industry. The importance of data mining in business can also be acknowledged by looking at the specific role of data mining in the industry. Some of these include:

● Direct marketing – identify prospects with the highest potential to become highly qualified leads and focus the marketing campaign on them to increase conversion rates.
● Market segmentation – the importance of data mining in marketing comes from its potential to help you identify these characteristics and segment the market more accurately.
● Minimize financial risks – some transactions are riskier than the others, with data mining, a company can identify the deals with the highest risk factor.
● Trend analysis – identify trends in customer behavior, sales trends, marketing performance, and so on.

6 Steps to Professional Data Mining

Now that you understand the importance of data mining in business, you are probably interested in the data mining process. Here are the six essential steps to follow for professional data mining.

1.Business Understanding

Data mining is a great practice, but it can’t help you if you use it just for the sake of using it. It’s essential to understand the business, discover and define specific goals, and identify which goals can be achieved with the help of data mining.

There are also constraints that have to be considered. For instance, if the documentation is not digitized, all the records are kept on paper and businesses will have to scan them before benefiting from data mining. When all of that is done, the data mining goals have to be set. These goals should reflect specific business objectives. Again when all those boxes on the list are checked, companies can proceed to make a data mining plan. This plan should incorporate strategies to help achieve both data mining and business goals.

2. Data Understanding

Data understanding begins with identifying the data sources relevant to the purposes the business wants to make.

Once the data sources have been identified, companies can start the initial data collection. The most critical processes in this phase are data load and data integration, as they are Download the image:

vital for successful data collection. As the data collection proceeds, companies have to keep close tabs on the data. It has to be under constant monitoring to ensure a high degree of quality – it has to be error-free, complete, and up to date.

3. Data Preparation

The recently collected data cannot be used for making business decisions. Before that can be done, it has to be processed. This process is called data preparation, and it usually takes up to 90% of the time needed for the completion of data mining.

The raw data has to undergo several phases. First, it has to be cleaned of excess and irrelevant data, and then it has to be formatted in the preferred form. This makes the following phase so much easier.

4. Data Modeling

After you’ve prepared the data, it can be modeled. The prepared data set can be shaped by several different techniques. Before continuing with modeling, every model has to be tested to ensure the relevancy and quality of the model.

In this phase, data mining experts often seek consultation from relevant stakeholders to ensure that models can be used without affecting any business initiatives.

5. Evaluation

In the evaluation phase, the modeled data set has to be double-checked in terms of its relevance to business objectives. Model results may indicate that new business objectives can be set. At this point, managers can decide whether to stick with the original plan or expand the scope of data mining.

6. Deployment

Finally, we have the deployment phase, where the stakeholders get the chance to see the reports, patterns, and other notable figures. Depending on the results, the company can decide to act on the report or adopt data mining as an ongoing project.
Hopefully, now you see the importance of data mining in business. The role of data mining in the industry is not only to help standardize data collection and storage protocols but also to empower businesses with meaningful information and help executives make informed decisions.

If you don’t have the internal team capable of carrying out complex data management projects, data management outsourcing always stays as a viable option. Data Entry Outsourced is the leader in the data entry and data management industry. The team of highly experienced data experts will help you make sure every data management project is delivered on time.